Sociodemographic and Anthropometric Factors Associated With Screen-Based Sedentary Behavior Among Japanese Adults: A Population-Based Cross-Sectional Study.

J Epidemiol 2013;23(5):382-388
doi:1 0.21 88/jea.JE201 30008

Original Article

Sociodemographic and Anthropometric Factors Associated With
Screen-Based Sedentary Behavior Among Japanese Adults:
A Population-Based Cross-Sectional Study

Kaori Ishii, Ai Shibata, and Koichiro Oka

Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
Received February 1, 2013; accepted May 28, 2013; released online July 27, 2013

Copyright © 2013 Kaori Ishii et al. This is an open access article distributed under the terms of Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ABSTRACT

Background: Concern over the health risks of sedentary behavior has highlighted the need to examine factors
associated with screen-based (television/computer) sedentary behavior. The present study examined the association
of screen-based sedentary behavior with body weight and sociodemographic attributes among Japanese adults.
Methods: A population-based cross-sectional study enrolled 1034 Japanese adults aged 40 to 69 years who lived in
2 Japanese cities. Sociodemographic variables, height, weight, and time spent on screen-based sedentary behavior
were collected by self-administered questionnaire. Differences in screen time in relation to body mass index and
weight gain since age 20 years were assessed by the Mann-Whitney U test. Independent associations of each variable
with screen time were examined by forced-entry logistic regression analyses.

Results: Mean (SD) age and median (interquartile range) duration of screen time per week were 55.6 (8.4) years
and 832.0 (368.8-1263.1) minutes, respectively, for men, and 55.3 (8.4) years and 852.6 (426.0-1307.5) minutes,
respectively, for women. Screen time among participants with weight gain was longer than among those with a
weight gain of less than 10 kg (P=0.08). Unmarried and unemployed participants had longer screen times.
Participants aged 40 to 49 years were less likely than older age groups to spend time on screen-based sedentary
behavior during leisure hours.

Conclusions: The present findings imply that strategies are necessary to discourage screen-based sedentary
behavior among all demographic groups, especially among adults who are elderly, unmarried, or unemployed.

Key words: weight status; Japanese; sedentary behavior; sociodemographic

INTRODUCTION

Recent studies have reported that the amount of leisure
time spent on discretionary screen-based sedentary behavior
(as opposed to that required during working hours), such
as television viewing and computer use, is associated with
increased risks of weight gain, type II diabetes, and
cardiovascular disease. 1 " 10 Sedentary behavior is defined
as activity that involves energy expenditure in the range of
1.0 to 1.5 metabolic equivalents (METs). 11 The mean time
spent by adults on screen-based sedentary behavior was
reported to be 188.0 minutes/day in Scotland 12 and 235.1
minutes/day in Australia. 13 Although screen-based sedentary
behavior is associated with health risks, a large proportion
of the population in developed countries is sedentary.
Reducing sedentary time increases opportunities to be

physically active, so it is important to focus on screen-based
sedentary behavior.

Physical activity guidelines 14 ' 15 and a recent global state-
ment 16 encourage a widespread, population-based approach to
decrease sedentary behavior. The guidelines emphasize the
consequences of sedentary behavior and the need to tailor
interventions to the requirements of specific population groups
such as children, adults, men, women, older persons, disabled
persons, employees, and diverse cultural groups. 14 ~ 16 Deter-
mining the amount of leisure time spent by specific population
groups on screen-based sedentary behavior is also important
when designing strategies to decrease such behavior.

Screen-based sedentary behavior has been investigated
among various demographic groups, especially in the United
States, Australia, and Europe. A systematic review found
that relationships between sedentary behavior and

Address for correspondence. Kaori Ishii, Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan (e-mail:
ishiikaori@aoni.waseda.jp).

382

Ishii K, et al.

383

sociodemographic status vary by country. Many studies on
the correlates of sedentary behavior have been conducted
among children, but studies of adults are less common.
The sociodemographic factors associated with screen-based
sedentary behavior among Japanese adults remain to be
determined. In addition, associations of anthropometric factors
such as body mass index (BM1) and weight gain with screen-
based sedentary behavior were less evident in the Japanese
population. The present study examined the associations of
sociodemographic and anthropometric factors with screen-
based sedentary behavior among adults in Japan.

METHODS

Participants and data collection

The present cross-sectional study was conducted from
February through March 2011. A total of 3000 residents
aged 40 to 69 years and living in 2 Japanese cities, Kanuma
and Nerima, were randomly selected from the residential
registries of those cities. Potential participants were stratified
by sex and age bracket (40^9, 50-59, and 60-69 years).
The plan was to include 1500 participants of each sex, 1000
participants from each age bracket, and 1500 participants from
each city. Nerima is an urban area within commuting distance
of Tokyo, while Kanuma is a mid-sized city in central Japan.
These 2 cities were chosen to reflect urban and suburban
lifestyles.

A self-administered questionnaire that included questions
on sociodemographic variables, sedentary behavior, height,
and weight was mailed to participants. To encourage a
response, letters explaining the study were sent to all par-
ticipants 2 weeks before the questionnaire. Nonresponders
were sent 1 reminder about the questionnaire. A total of 1105
participants replied to the questionnaire (36.8% overall
response rate; 33.8% from Kanuma and 37.9% from
Nerima). All participants signed an informed consent
document before answering the questionnaire. The Ethics
Committee of Waseda University, Japan approved the study
before its commencement.

Measures

Sociodemographic factors

Participants provided information on sociodemographic
factors such as sex, age, education level, employment status,
marital status, living arrangements, and household income
level by choosing the most suitable response from a set of
predetermined options, as follows: education level (graduate
school or university, 2 years of university education or
equivalent, college, high school, or junior high school),
employment status (full-time, part-time, full-time homemaker,
student, or unemployed), marital status (married or
unmarried), living arrangements (cohabitating or living
alone), and household income level (<3, >3-<5, >5-<7,
>7-<10, or >10 million yen).

Anthropometric variables

BMI was calculated from self-reported height and weight.
Weight gain since age 20 years was estimated from self-
reported weight at age 20 years.
Screen-based sedentary behavior

Participants reported duration of screen-based sedentary
behavior over a usual week (screen time). Screen-based
sedentary behavior comprised computer and Internet use for
leisure purposes, television watching, computer gaming,
and video or DVD watching. 13 ' 18 Participants were asked
how many times per week they spent on screen time and
the duration of screen time on each of those days. The
scale was previously shown to have acceptable reliability
and validity. 18 The test-retest reliability of the items was
found to be moderate (range 0.6-0.8). Validity, as defined
by correlations with 3 -day behavioral log data, was moderate
(range 0.3-0.6). The total time spent on screen time was
classified as low or high, based on the median of 841.8
minutes/week.

Statistical analyses

Differences in participant characteristics and screen time
were compared by sex and city with the Mest, x 2 test, and
Mann- Whitney U test. Differences in screen time between
those with a BMI of less than 25kg/m 2 versus 25kg/m 2
or higher, and those with a weight gain of less than
10 kg versus 10 kg or more, since age 20 were assessed by
the Mann-Whitney U test. Forced-entry logistic regression
analyses were conducted to examine independent relation-
ships of each sociodemographic variable with screen time.
Responses to sociodemographic attributes were categorized as
follows: sex (male or female), age (40^9, 50-59, and 60-69
years), education level (>4 years of university education,
2 years of university education or equivalent, or high school
or junior high school), employment status (employed or
not employed), marital status (married or unmarried),
living arrangements (living with another individual or living
alone), and household income level (<3, >3-<5, >5-<7,
>7-<10, or >10 million yen). All statistical analyses were
performed with SPSS 18.0J for Windows (Statistical Package
for the Social Sciences; SPSS Inc. Chicago, IL, USA). A P
value of less than 0.05 was considered to indicate statistical
significance.

RESULTS

Sociodemographic characteristics of participants

Data from the 1034 adults (540 men and 494 women) who
fully completed the survey were included in the analysis.
Table 1 shows the sociodemographic characteristics of the
study participants. Mean (SD) age for men was 55.6 (8.4)
years, and mean age for women was 55.3 (8.4) years. The
proportions of married male and female respondents were
84.2% and 85.0%, respectively; 91.3% and 94.1%,

J Epidemiol 2013;23(5):382-388

384

Table 1.

Factors Associated With Screen-Based Sedentary Behavior in Japan
Sociodemographic characteristics of respondents

Men Women Nerima Kanuma

n

%

n

%

P value

n

%

n

%

P value

Overall

540

100.0

494

100.0

548

52.7

491

47.3

Age group (years)

40-49

149

27.6

149

30.2

153

27.9

146

29.7

50-59

189

35.0

164

33.2

0.645

175

31.9

178

36.3

0.115

60-69

202

37.4

181

36.6

220

40.1

167

34.0

Mean ± SD

55.6 ±8.4

55.3 ±8.4

0.637

55.8 ±8.5

55.1 ±8.3

0.190

Marital status

Unmarried

85

15.8

74

15.0

0.731

89

16.3

71

14.5

0.440

Married

453

84.2

419

85.0

458

83.7

418

85.5

Living condition

Living with others

493

91.3

465

94.1

0.095

498

90.9

464

94.5

0.032

Living alone

47

8.7

29

5.9

50

9.1

27

5.5

Education level

4 or more years of university

246

45.6

90

18.2

250

45.6

87

17.7

2 years of university or equivalent

51

9.4

160

32.4

<0.001 a

120

21.9

93

18.9

<0.001 a

High school or junior high school

243

45.0

244

49.4

178

32.5

311

63.3

Employment status

Employed

462

85.6

304

61.5

<0.001 a

403

73.5

367

74.7

0.671

Not employed

78

14.4

190

38.5

145

26.5

124

25.3

Household income level (yen)

<3 000 000

104

19.3

127

25.7

105

19.2

129

26.3

<5 000 000

149

27.6

140

28.3

145

26.5

144

29.3

<7 000 000

109

20.2

97

19.6

0.066

102

18.6

104

21.2

<0.001 a

<1 0000 000

104

19.3

78

15.8

108

19.7

76

15.5

>1 0000 000

74

13.7

52

10.5

88

16.1

38

7.7

BMI

<25 kg/m 2

373

69.1

414

83.8

<0.001 a

433

79.0

356

72.5

0.016

>25 kg/m 2

167

30.9

80

16.2

115

21.0

135

27.5

Mean ± SD

23.7 ±3.0

22.3 ±3.3

<0.001 b

22.6 ± 3.2

23.4

±3.2

<0.001 b

Weight gain

<10kg

376

69.6

422

85.4

<0.001 a

425

77.7

373

76.6

0.711

>10kg

164

30.4

72

14.6

122

22.3

114

23.4

Mean ± SD

7.1 ±7.8

3.9 ±7.5

<0.001 b

5.3 ±7.7

5.8 ±8.0

0.307

Screen time, min/week

Median (interquartile range)

S3? 0

85? fi

840 0

848.5

0.517°

(368.8-1263.1)

(426.0-1307.5)

0.041 c

(408.4-1269.8)

(393.9-1269.2)

All values are n (%) unless indicated otherwise. Groups compared by using the (a) % 2 test, (b) West, or (c) Mann-Whitney U test.
BMI: body mass index.

respectively, lived with other people and 85.6% and 61.5%,
respectively, were employed. Median (interquartile range
[IQR]) screen time per week among men and women was
832.0 (368.8-1263.1) and 852.6 (426.0-1307.5) minutes,
respectively. Significant differences were observed between
men and women in BMI, weight gain, screen time, education
level, and employment status. Significant differences were
observed between urban and suburban areas in BMI, living
arrangements, education level, and household income level;
however, no differences in age, marital status, employment
status, weight gain, or screen time were observed between
areas.

Association between screen time and weight status

Median (IQR) screen time/week was 843.8 (403.8-1265.6)
among participants with a BMI of less than 25 kg/m 2 and
842.9 (405.0-1403.3) among those with a BMI of 25 kg/m 2
or higher. The association between screen time and BMI was

not statistically significant (P = 0.24). Median screen time per
week was greater among participants with a weight gain of
10kg or more (median = 844.8; IQR, 425.6-1357.5) than
among those with a weight gain of less than 10 kg since age
20 (841.8, 386.3-1266.6) (P=0.08).

Association between screen time and demographic
variables

Table 2 shows the results of adjusted logistic regression
analysis. Unmarried participants (odds ratio [OR], 2.02; 95%
CI, 1.32-3.10) and unemployed participants (OR, 1.63; 95%
CI, 1.19-2.23) were significantly more likely to spend more
time on screen-based sedentary behavior. Participants aged
40 to 49 years (OR, 0.64; 95% CI, 0.46-0.89) reported less
screen time during leisure hours than did those aged 60 to 69
years. Screen time was not significantly associated with sex,
living arrangements, education level, or household income
level.

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Ishii K, et al.

385

Table 2. Multiple logistic regression analyses of socio-
demographic correlates of screen-based sedentary
behavior

OR 95% CI P value

Sex

Men

0.99

0.75-

-1.31

0.96

Women

1.00

Age group (years)

4CM9

0.64

0.46-

-0.89

0.01

50-59

0.79

0.57-

-1.09

0.15

60-69

1.00

Marital status

IVIQI ILQI OLC^IUO

Unmarried

2.02

1.32-

-3.10

0.001

MarripH

I via 1 1 icu

1 .00

Living condition

Living with others

1.59

0.89-

-2.81

0.12

Living alone

1.00

Educational level

4 or more years of university

0.80

0.59-

-1.09

0.16

2 years of university or equivalent

0.97

0.69-

-1.37

0.86

High school or junior high school

1.00

Employment status

Not employed

1.63

1.19-

-2.23

0.001

Employed

1.00

Household income level (yen)

<3 000 000

1.21

0.74-

-2.00

0.44

<5 000 000

1.15

0.73-

-1.82

0.55

<7 000 000

1.31

0.82-

-2.11

0.26

<1 0000 000

1.41

0.88-

-2.26

0.16

>1 0000 000

1.00

OR: odds ratio.

Odds ratios were calculated after adjustment for all variables listed in
the table.

DISCUSSION

The present study examined the association of socio-
demographic and anthropometric factors such as body
weight and weight gain with screen-based sedentary
behavior among Japanese adults. The results revealed that
the level of screen-based sedentary behavior varied between
population subgroups: individuals who were older, unmarried,
or unemployed reported more screen time during their leisure
hours.

The present study focused only on leisure screen time
rather than total screen-related sedentary behavior. Sedentary
behavior tends to occur at specific time points and in
specific contexts. Thus, it is difficult to ascertain all the
details of such behavior. Furthermore, sedentary behavior is
relatively independent of physical activity, and both sedentary
and active behaviors can occur at any time of the day. 5 In
addition, determinants associated with sedentary behavior
differ by specific domain, such as leisure time versus working
time. 19 It is thus important to determine when sedentary
behavior occurs and to study certain specific time periods,
such as leisure time. 20 ' 21

The median duration of screen time in the present study was
841.8 minutes/week (about 120.6 minutes/day). In contrast,

duration of screen time was 188.0 minutes/day in Scotland
and 235.1 minutes/day in Australia 13 ; thus, duration of screen
time was shorter in Japan than in other countries. However,
the present values for screen time were based on participant
recall of the number of days spent on screen time during the
previous 7 days and the average amount of screen time on
each of those days. Thus, we cannot directly compare the
present results with those of studies that used different
methods to measure duration of screen time, and our results
should be interpreted with caution.

From the present results, association between screen time
and weight gain since age 20 were found among Japanese
adults. By contrast, BMI was not associated with screen time,
because only a small percentage of participants had a BMI of
25 kg/m 2 or higher. In Japan, although the rate of overweight/
obesity has rapidly increased during the past decade, 22 it is
low in comparison with other developed countries. In other
developed countries and Japan, body weight is positively
associated with the risks of lifestyle-related disease and
mortality. 23 Therefore, it was important to determine the
sociodemographic correlates of screen time associated with
weight status in the present study.

The present study found a positive association between
screen time and age. Because previous studies assessed
different age groups of adults, care should be taken in
interpreting the present findings and comparing them with
the results of earlier studies. Previous studies also reported
that screen -based sedentary behavior differed by age 7 ' 24 ~ 28 ;
however, those studies found no consistently significant
relationship between age and general screen-based sedentary
behavior. 17 The results of the present study show a strong
relationship between age and screen time. Therefore,
interventions should aim to decrease leisure-time sedentary
behavior among older Japanese adults.

Marriage, or a long-term relationship, significantly
contributes to individual quality of life. 29 The present study
found that unmarried participants tended to report more screen
time. Social support strongly correlates with physical activity
level and enhances well-being. Being married is associated
with an increased likelihood of engaging in health-promoting
behaviors such as exercise, presumably because marital
partners exert influence over each other's behavior. 21
However, a previous study found that the association
between marital status and screen-based sedentary behavior
was weak and that more evidence was needed. 17 Thus, the
results of the present study are important evidence for an
association between marital status and screen-based sedentary
behavior.

A previous study 17 provided evidence of a positive
relationship between TV viewing (as part of screen-based
sedentary behavior) and being unemployed, but associations
between other sedentary behaviors and employment status
were less clear. In the present study, unemployed individuals
were more likely to report greater screen time. Studies that

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386

Factors Associated With Screen-Based Sedentary Behavior in Japan

examined correlates of physical activity among Japanese
adults found that unemployed adults were more likely than
employed persons to engage in moderate-to-vigorous physical
activity. 30 ' 31 Therefore, when designing interventions to
promote the health of unemployed persons, measures to
decrease screen-based sedentary behavior may be required, in
addition to those aimed at increasing an already high level of
physical activity.

Living arrangements, sex, education level, and household
income level were not associated with screen time in the
present study. Participants were not asked for detailed
information about the persons they lived with or about the
nature of their relationship. Hence, the explanatory power of
this information is limited; participants who answered that
they lived with other people may be living with parents,
siblings, or children, among other possibilities. A previous
study 17 reported that current evidence of an association
between living with a child and engaging in sedentary
behavior was scant. However, only a limited number of
studies have investigated this issue; further studies are needed
to confirm any association between screen time and living
arrangements.

The present study did not find a statistically significant
sex difference in duration of screen-based sedentary behavior.
Some previous studies found no evidence of a sex difference
in screen-based sedentary behavior 32-38 ; however, other
studies reported that the amount of screen time was greater
among men than among women. 7 ' 27 ' 39 ' 40 Therefore, any
approach to discourage screen time during leisure hours
may need to target both Japanese women and men.

Socioeconomic status may be a key factor in determining
the health status of an individual. A systematic review 17 of
data from other countries summarized associations between
education, income, and screen-based sedentary behavior. The
authors suggested that the association between income and
TV viewing was inconclusive, that there was no association
between income and amount of computer use, and that
educational level may be inversely associated with TV
viewing and positively associated with computer use.
However, in the present study, neither education status nor
household income level were associated with screen time.
Therefore, to decrease sedentary behavior in relation to
educational status and household income level, an effective
approach might be to focus on screen-based sedentary
behavior in the relevant segments of the Japanese adult
population.

The present study had limitations. First, the cross-sectional
nature of the study limits conclusions regarding the causality
of observed relationships of sociodemographic and anthro-
pometric factors with screen time. Second, to estimate screen
time, the study relied on self-reported measures that are
subject to error, owing to different interpretations of the
questions. 41 ' 42 In addition, the reliability and validity of the
scale have yet to be demonstrated in Japan. Third, the study

respondents slightly differed from the general population.
To estimate the representativeness of participant responses,
the adjusted prevalences of marital and employment statuses,
by age bracket, were compared with data from the Japanese
Population Census Survey of 2005. 43 In the 2 surveys, the
prevalence of married participants was 84.2% and 63.5%,
respectively, among men and 85.0% and 63.8% among
women. Regarding employment status, 85.6% and 66.3% of
men, and 61.5% and 34.9% of women, respectively, worked
full-time or part-time. 44 Therefore, the basic characteristics of
respondents might have been biased, and the findings in such
a setting may not be applicable to the general population.
However, the characteristics of the present population are
sufficiently similar to those of the general population because
the present study randomly selected participants from a
registry of residential addresses of each city, which allowed
an equal number of responses to be obtained from both sexes
and from each age group category between age 40 and age
69 years. Fourth, the study included only participants aged
40 to 69 years, so the generalizability of the present study
findings to other age groups is unclear and requires further
assessment.

Despite these limitations, few studies have examined the
present topic among a randomly selected Japanese population.
The present findings increase understanding of the
determinants of screen time and may help in developing
new strategies and interventions to promote public health and
well-being in Japan.

Conclusions

The present study identified sociodemographic and anthro-
pometric factors associated with leisure-time screen-based
sedentary behavior among Japanese adults. In the absence
of similar studies in Japan, the present results will help in
developing interventions to promote health and discourage
screen-based sedentary behavior by targeting important
determinants of sedentary pursuits in all sociodemographic
groups, and especially among elderly, unmarried, and
unemployed adults.

ONLINE ONLY MATERIALS

Abstract in Japanese.

ACKNOWLEDGMENTS

This study was supported in part by the National Cancer
Center Research and Development Fund (23-A-5); Grants-in-
Aid for Scientific Research (No. 22700681) from the Japan
Society for the Promotion of Science; and the Global COE
Program "Sport Sciences for the Promotion of Active Life"
from the Japan Ministry of Education, Culture, Sports,
Science and Technology.

Conflicts of interest: None declared.

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Ishii K, et al.

387

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